The Data Science for Social Good mentors are the core of the fellowship. As experienced data scientists from industry and academia, the mentors bring both technical knowledge and real-world experience to the program. They’re helpful guides for the fellows and their projects, and liaisons for the partner organizations. Finding the right people with both technical skills and an interest in social issues is no easy task; we’re pleased to have found several such individuals to join us this summer.
Kate Cagney is an associate professor of sociology and health studies at the University of Chicago, and director of the Population Research Center at the National Opinion Research Center. Cagney’s work examines social inequality and its relationship to health with a focus on neighborhood, race, aging, and the life course. She has developed a series of papers on neighborhood social capital and its relationship to outcomes such as self-rated health, asthma prevalence, physical activity, and mortality during the 1995 Chicago heat wave. Currently she works on two Chicago-based studies of neighborhood context and older adult health, examines the role of the social and physical environment in older adult well-being with the National Social Life, Health, and Aging Project, and has started research on the social impact of the upcoming Chicago Lakeside Development, a 600-acre, entirely new neighborhood that will be built on Chicago’s South Side.
Varun Chandola is an Assistant Professor at University at Buffalo (SUNY) in the Computer Science Department, where he is part of an NSF-funded center for Computational and Data-Enabled Science and Engineering. His research covers the application of data mining and machine learning to problems involving big and complex data, focusing on anomaly detection — finding surprising patterns, connections, associations, and trends in data. Previously, Chandola worked as a scientist at Oak Ridge National Laboratory, seeking analytic solutions for climate, sustainability, and health care.
Matt Gee is a co-founder of the Data Science for Social Good fellowship and a 2012 MPP graduate of the Harris School of Public Policy. He works at the intersection of computer science, economics, and public policy, and spends half his time doing original research in computational social science and the other half building practical tools aimed at solving real-world problems with data. He directs the Center for Impact Measurement, co-founded Effortless Energy, the new Chicago Policy Review, and the Harris Energy Association, and he currently leads the Chicago School of Data project. His areas of focus include computational social science, climate policy, energy use behavior, science and technology policy, housing, and program evaluation.
Young-Jin Kim is the founder and managing director of Emphanos, a technology consulting company that specializes in providing open source data management solutions to the nonprofit and government sector. After graduating from the University of Chicago, where he studied physics, he developed software systems for computer aided diagnosis and data analysis tools in medical physics, analyzed and fused large messy geospatio-temporal data sets while a graduate student in geophysical sciences at UChicago, and conducted research at Cambridge University, Woods Hole Oceanographic Institute, and in Antarctica. His interests are in image analysis, data mining, evolutionary algorithms, computational fluid dynamics, inverse problems, and open source software development. At Emphanos, he deploys open source tools to solve data integration and system integration problems that help nonprofits advance their mission.
Tom Plagge returns for his second year as a DSSG mentor. Tom studied astrophysics at UC Berkeley, doing his thesis work on a millimeter-wave telescope at the South Pole. He came to the University of Chicago as a post-doctoral researcher in 2009, continuing his work on astrophysics instrumentation and data analysis with the CARMA telescope array. He joined the 2013 DSSG fellowship to lead the Cook County Land Bank and Chicago Public Safety projects, and has continued on with the new Center for Data Science and Public Policy a joint center of the Computation Institute and the Harris School of Public Policy. His research interests include urban planning and development, energy efficiency, and public health.
Eric Rozier is an Assistant Professor of Electrical and Computer Engineering at the University of Miami, specializing in Big Data, Systems Engineering, and Cybersecurity/Privacy. His research focuses on improving system infrastructure for long term curation of climate and longitudinal data and the processing of private data. Additionally, he has collaborated with NOAA climate scientists, Medecins sans Frontieres, and the African Great Lakes Initiative on using computer science to tackle social problems. At Miami University, Rozier is developing a new curriculum on Big Data, and is interested in connected students to real tools, data, and resources to solve industrial problems.
Joe Walsh is a 2013 Data Science for Social Good fellow returning this summer as a DSSG mentor. Walsh has worked as lead forecaster for GE Healthcare’s marketing department and as a statistical consultant for the National Labor Relations Board. His research has examined the politics of the Medal of Honor, the timing of political press releases, motorcycle crash injuries, the relationship between transportation and peace in sub-Saharan Africa, and hockey fights. With DSSG last summer, he worked on a project with Nurse-Family Partnership to measure the impact of the national program.
Ben Yuhas is principal at Yuhas Consulting Group, which he formed to serve a broad spectrum of commercial and non-profit clients. His background is in predictive modeling, and he received his BA in mathematics from the UChicago and his PhD in electrical and computer engineering at Johns Hopkins. After several years building models to predict consumer behavior in financial services, he migrated those skills into the political realm and formed his consulting business. In recent years, Yuhas worked to bring the sophistication of data-driven strategies to fundraising and voter mobilization, including micro-targeting models for the get-out-the-vote efforts of the 2004 John Kerry presidential campaign and the 2005 election of Virginia Governor Tim Kaine.